A cell simulator platform: the cell collective.
Ontology highlight
ABSTRACT:
SUBMITTER: Helikar T
PROVIDER: S-EPMC5242230 | biostudies-literature | 2013 May
REPOSITORIES: biostudies-literature
Publications
A cell simulator platform: the cell collective.
Helikar T T Kowal B B Rogers J A JA
Clinical pharmacology and therapeutics 20130220 5
Diseases are often a result of multiple malfunctions in complex, nonlinear biological/biochemical networks. As such, these processes are far more complicated to understand because they tend to give rise to functions that are emergent in nature, i.e., higher-level (mal)functions that are more than the sum of their parts. Systems biology provides a new approach to understanding biological systems and diseases from a holistic perspective. ...[more]
Similar Datasets
Project description:Tumor local invasion is the first step of metastasis cascade which remains the key obstacle for cancer therapy. Collective cell migration plays a critical role in tumor invading into surrounding tissues. In vitro assays fail to assess collective invasion in a real time manner. Herein we aim to develop a three-dimensional (3D) microfluidic cell invasion model to determine the dynamic process. In this model, collective invasion of breast cancer cells is induced by the concentration gradient of fetal bovine serum. We find that breast cancer cells adopt a collective movement rather than a random manner when the cells invade into extracellular matrix. The leading cells in the collective movement exhibit an increased expression of an Aurora kinase family protein - AURKA compared with the follower cells. Inhibition of AURKA kinase activity by VX680 or AKI603 significantly reduces the phosphorylation of ERK1/2 (Thr202/Tyr204) and collective cohort formation. Together, our study illustrates that AURKA acts as a potential therapeutic target for suppressing the process of tumor collective invasion. The 3D microfluidic cell invasion model is a reliable, measurable and dynamic platform for exploring potential drugs to inhibit tumor collective invasion.
| S-EPMC5462816 | biostudies-other
Project description:Over the past half-century, ultrasound imaging has become a key technology for assessing an ever-widening range of medical conditions at all stages of life. Despite ultrasound's proven value, expensive systems that require domain expertise in image acquisition and interpretation have limited its broad adoption. The proliferation of portable and low-cost ultrasound imaging can improve global health and also enable broad clinical and academic studies with great impact on the fields of medicine. Here, we describe the design of a complete ultrasound-on-chip, the first to be cleared by the Food and Drug Administration for 13 indications, comprising a two-dimensional array of silicon-based microelectromechanical systems (MEMS) ultrasonic sensors directly integrated into complementary metal-oxide-semiconductor-based control and processing electronics to enable an inexpensive whole-body imaging probe. The fabrication and design of the transducer array with on-chip analog and digital circuits, having an operating power consumption of 3 W or less, are described, in which approximately 9,000 seven-level feedback-based pulsers are individually addressable to each MEMS element and more than 11,000 amplifiers, more than 1,100 analog-to-digital converters, and more than 1 trillion operations per second are implemented. We quantify the measured performance and the ability to image areas of the body that traditionally takes three separate probes. Additionally, two applications of this platform are described-augmented reality assistance that guides the user in the acquisition of diagnostic-quality images of the heart and algorithms that automate the measurement of cardiac ejection fraction, an indicator of heart health.
| S-EPMC8271708 | biostudies-literature
Project description:To meet the need for "standard" testing system for wearable blood pressure sensors, this study intends to develop a new radial pulsation simulator that can generate age-dependent reference radial artery pressure waveforms reflecting the physiological characteristics of human cardiovascular system. To closely duplicate a human cardiovascular system, the proposed simulator consists of a left ventricle simulation module, an aorta simulation module, a peripheral resistance simulation module, and a positive/negative pressure control reservoir module. Simulating physiologies of blood pressure, the compliance chamber in the simulator can control arterial stiffness to produce age-dependent pressure waveforms. The augmentation index was used to assess the pressure waveforms generated by the simulator. The test results show that the simulator can generate and control radial pressure waveforms similar to human pulse signals consisting of early systolic pressure, late systolic pressure, and dicrotic notch. Furthermore, the simulator's left ventricular pressure-volume loop results demonstrate that the simulator exhibits mechanical characteristics of the human cardiovascular system. The proposed device can be effectively used as a "standard" radial artery pressure simulator to calibrate the wearable sensor's measurement characteristics and to develop more advanced sensors. The simulator is intended to serve as a platform for the development, performance verification, and calibration of wearable blood pressure sensors. It will contribute to the advancement of the wearable blood pressure sensor technology, which enables real-time monitoring of users' radial artery pressure waveforms and eventually predicting cardiovascular diseases.
| S-EPMC6388329 | biostudies-other
Project description:Background: Adaptive designs and platform designs are among two common clinical trial innovations that are increasingly being used to manage medical intervention portfolios and attain faster regulatory approvals. Planning of adaptive and platform trials necessitate simulations to understand how a set of adaptation rules will likely affect the properties of the trial. Clinical trial simulations, however, remain a black box to many clinical trials researchers who are not statisticians. Results: In this article we introduce a simple intuitive open-source browser-based clinical trial simulator for planning adaptive and platform trials. The software application is implemented in RShiny and features a graphical user interface that allows the user to set key clinical trial parameters and explore multiple scenarios such as varying treatment effects, control response and adherence, as well as number of interim looks and adaptation rules. The software provides simulation options for a number of designs such as dropping treatment arms for futility, adding a new treatment arm (i.e., platform design), and stopping a trial early based on superiority. All available adaptations are based on underlying Bayesian probabilities. The software comes with a number of graphical outputs to examine properties of individual simulated trials. The main output is a comparison of trial design performance across several simulations, graphically summarizing type I error (false positive risk), power, and expected cost/time to completion of the considered designs. Conclusion: We have developed and validated an intuitive highly efficient clinical trial simulator for planning of clinical trials. The software is open-source and caters to clinical trial investigators who do not have the statistical capacity for trial simulations available in their team. The software can be accessed via any web browser via the following link: https://mtek.shinyapps.io/hect/.
| S-EPMC6556760 | biostudies-literature
Project description:Glioblastoma is the most aggressive malignant brain tumor with poor survival due to its invasive nature driven by cell migration, with unclear linkage to transcriptomic information. Here, we applied a physics-based motor-clutch model, a cell migration simulator (CMS), to parameterize the migration of glioblastoma cells and define physical biomarkers on a patient-by-patient basis. We reduced the 11-dimensional parameter space of the CMS into 3D to identify three principal physical parameters that govern cell migration: motor number - describing myosin II activity, clutch number - describing adhesion level, and F-actin polymerization rate. Experimentally, we found that glioblastoma patient-derived (xenograft) (PD(X)) cell lines across mesenchymal (MES), proneural (PN), classical (CL) subtypes and two institutions (N=13 patients) had optimal motility and traction force on stiffnesses around 9.3kPa, with otherwise heterogeneous and uncorrelated motility, traction, and F-actin flow. By contrast, with the CMS parameterization, we found glioblastoma cells consistently had balanced motor/clutch ratios to enable effective migration, and that MES cells had higher actin polymerization rates resulting in higher motility. The CMS also predicted differential sensitivity to cytoskeletal drugs between patients. Finally, we identified 11 genes that correlated with the physical parameters, suggesting that transcriptomic data alone could potentially predict the mechanics and speed of glioblastoma cell migration. Overall, we describe a general physics-based framework for parameterizing individual glioblastoma patients and connecting to clinical transcriptomic data, that can potentially be used to develop patient-specific anti-migratory therapeutic strategies generally.Significance statementSuccessful precision medicine requires biomarkers to define patient states and identify personalized treatments. While biomarkers are generally based on expression levels of protein and/or RNA, we ultimately seek to alter fundamental cell behaviors such as cell migration, which drives tumor invasion and metastasis. Our study defines a new approach for using biophysics-based models to define mechanical biomarkers that can be used to identify patient-specific anti-migratory therapeutic strategies.
| S-EPMC9980090 | biostudies-literature
Project description:The most important step in any quantitative proteomic pipeline is feature detection (aka peak picking). However, generating quality hand-annotated data sets to validate the algorithms, especially for lower abundance peaks, is nearly impossible. An alternative for creating gold standard data is to simulate it with features closely mimicking real data. We present Mspire-Simulator, a free, open source shotgun proteomic simulator that goes beyond previous simulation attempts by generating LC-MS features with realistic m/z and intensity variance along with other noise components. It also includes machine learned models for retention time and peak intensity prediction and a genetic algorithm to custom fit model parameters for experimental data sets. We show that these methods are applicable to data from three different mass spectrometers, including two fundamentally different types, and show visually and analytically that simulated peaks are nearly indistinguishable from actual data. Researchers can use simulated data to rigorously test quantitation software, and proteomic researchers may benefit from overlaying simulated data on actual data sets. While not directly relevant in this case, a search was conducted by Proteome-Discoverer v1.4 by both mascot and Sequest-HT. The parameters included 2 missed cleavages by Trypsin, carboamidomethylation of the Cysteines, Phosphorylations of STY residues, and Oxidations of HW residues, and at a precursor mass tolerance of 10 ppm.
2020-01-24 | PXD000477 | Pride
Project description:Theory:Individuals have different qualities, levels of willingness, and degrees of engagement for working in teams. This behaviour is termed 'Collective Orientation' (CO). Collective orientation can be trained and has a positive influence on team processes. Here, we investigated the effect of a simulator-based, Crisis Resource Management team training upon the participants' CO. Hypotheses:We hypothesized (1) the scales of CO and Presence for lab-based microworld research (PLBMR) are applicable to the German anaesthesia teams, (2) the CO can be influenced by means of simulation training, (3) the training effect is dependent on sex and/or profession, and (4) the change of CO depends on the perceived presence of the participants in the scenario. Method:In a pre-post study, 66 nurses and doctors from various anaesthetic departments took part in a 1-day training course to improve non-technical skills. The primary outcome was the mean difference between the CO measured (via questionnaires) immediately before (T1) and after (T2) training. The change was then tested for dependence upon other variables, such as sex, professional group, and immersion into the simulation scenarios. Results:Collective orientation improved significantly after training (mean difference: 0.2; P?<?.001; dz?=?0.53). Considering the subscales, affiliation increased significantly (P?<?.001; dz?=?0.59), whereas dominance remained unchanged. Furthermore, no correlation was found regarding sex, professional group, or immersion into the simulation scenarios. Conclusions:Our study demonstrated that simulation-based training improves the participants' COs, primarily by increasing affiliation. Subjective scenario reality did not significantly influence this. Nonetheless, it remains unclear as to what factors categorically resulted in this benefit. The shared experience in the course by all team members might trigger the effects. However, further studies are needed to identify the modifiable factors that can improve teamwork attitudes.
| S-EPMC7309374 | biostudies-literature
Project description:Collective cell movements contribute to development and metastasis. The small GTPase Rac is a key regulator of actin dynamics and cell migration but the mechanisms that restrict Rac activation and localization in a group of collectively migrating cells are unknown. Here, we demonstrate that the small GTPases Rab5 and Rab11 regulate Rac activity and polarization during collective cell migration. We use photoactivatable forms of Rac to demonstrate that Rab11 acts on the entire group to ensure that Rac activity is properly restricted to the leading cell through regulation of cell-cell communication. In addition, we show that Rab11 binds to the actin cytoskeleton regulator Moesin and regulates its activation in vivo during migration. Accordingly, reducing the level of Moesin activity also affects cell-cell communication, whereas expressing active Moesin rescues loss of Rab11 function. Our model suggests that Rab11 controls the sensing of the relative levels of Rac activity in a group of cells, leading to the organization of individual cells in a coherent multicellular motile structure.
| S-EPMC4006229 | biostudies-literature
Project description:Collective cell motility is an important aspect of several developmental and pathophysiological processes. Despite its importance, the mechanisms that allow cells to be both motile and adhere to one another are poorly understood. In this study we establish statistical properties of the random streaming behavior of endothelial monolayer cultures. To understand the reported empirical findings, we expand the widely used cellular Potts model to include active cell motility. For spontaneous directed motility we assume a positive feedback between cell displacements and cell polarity. The resulting model is studied with computer simulations and is shown to exhibit behavior compatible with experimental findings. In particular, in monolayer cultures both the speed and persistence of cell motion decreases, transient cell chains move together as groups and velocity correlations extend over several cell diameters. As active cell motility is ubiquitous both in vitro and in vivo, our model is expected to be a generally applicable representation of cellular behavior.
| S-EPMC3044241 | biostudies-literature
Project description:A distinct highly invasive subpopulation was identified in breast cancer cell lines. The molecular characteristics of these cells was investigated, revealing a set of genes whose high expression confers the ability to invade. Total RNA isolated from the invasive subpopulation from 2 cells lines was compared to total RNA isolated from 2 noninvasive populations.
2014-06-19 | E-GEOD-58643 | biostudies-arrayexpress